Optimizing PLC Electrical Performance for Maximum Productivity

1. Introduction

1.1 Research background and significance

In the modern industrial field, Programmable Logic Controller (PLC) has become a key device for realizing automated production and is widely used in many industries such as manufacturing, energy, and transportation. From automobile manufacturing production lines to process control in chemical companies to automated management of smart buildings, PLCs are everywhere, taking on core tasks such as data processing, logic control, and device driving. With the rise of Industry 4.0 and the concept of smart manufacturing, production systems have increasingly higher requirements for efficiency, reliability, and flexibility, making the optimization of PLC electrical performance a key factor in improving industrial productivity.

PLC realizes the automation and intelligence of the production process through precise logic control and fast data processing capabilities, effectively improving production efficiency. In traditional industrial control systems, the logic control circuits composed of hardware devices such as relays and contactors are not only bulky and complex in wiring, but also have slow response speed and low reliability. PLC adopts a digital control method and replaces hardware wiring with software programming, which greatly simplifies the design and maintenance of the control system and significantly improves the control accuracy and response speed. In automobile manufacturing production lines, PLC can accurately control the movements of robots to achieve fast and accurate assembly of parts, greatly improving production efficiency; in chemical production processes, PLC can monitor and adjust various process parameters in real time to ensure the safety of the production process. Stable operation, improve product quality and production efficiency.

Optimizing the electrical performance of PLC plays a vital role in improving production efficiency. On the one hand, by improving the computing speed and data processing capabilities of PLC, the response time of the system can be shortened, so that the equipment can respond to production instructions more quickly, thereby improving production efficiency. On high-speed assembly lines, PLC can quickly process signals from sensors, control the movement of equipment in a timely manner, ensure continuous production of products, and reduce production downtime. On the other hand, optimizing the electrical performance of PLC can also improve the reliability and stability of the system, reduce equipment failures and downtime, and thus ensure the continuity of production. The use of technologies such as redundant power supply and hot standby CPU can improve the fault tolerance of the PLC system. Even if some hardware fails, the system can still operate normally to ensure that production is not affected.

With the continuous improvement of industrial automation, the performance requirements of production systems for PLC are also increasing. In the future, PLC will develop towards higher performance, higher reliability and more intelligence. Therefore, in-depth research on PLC electrical performance optimization technology has important practical significance and application value for promoting the development of industrial automation and improving the competitiveness of enterprises.

1.2 Research objectives and problem solving

This study aims to explore how to optimize the electrical performance of PLC to maximize the improvement of industrial production efficiency. Through the research and improvement of PLC hardware, software and system architecture, a series of practical optimization strategies and methods are proposed to provide technical support and theoretical guidance for industrial enterprises to apply PLC in actual production.

In the process of optimizing the electrical performance of PLC, many key issues are faced. First, with the continuous expansion of industrial production scale and the increasing complexity of production processes, the amount of data and control tasks that PLC needs to process has increased dramatically, which has put higher requirements on its computing speed and data processing capabilities. How to improve the computing speed of PLC so that it can process large amounts of data quickly and accurately has become an urgent problem to be solved. In high-speed production lines, PLC needs to process a large amount of sensor data in real time and accurately control the movement of equipment to ensure production continuity and product quality. If the computing speed of PLC is insufficient, it will cause data processing delays, affect the response speed of the equipment, and thus reduce production efficiency.

Secondly, the reliability and stability of PLC are the key to ensuring production continuity. In industrial production environments, PLCs are often faced with various interference factors, such as electromagnetic interference, temperature changes, humidity, etc. These factors may cause PLC failures and affect the normal production. Therefore, how to improve the anti-interference ability of PLC and enhance its reliability and stability is an important issue in optimizing the electrical performance of PLC. In chemical companies, the electromagnetic interference in the production environment is more serious. If the anti-interference ability of PLC is insufficient, it is easy to cause malfunctions, leading to production accidents.

In addition, the communication compatibility between PLC and other devices is also an important issue. In modern industrial automation systems, PLCs usually need to communicate with a variety of devices, such as sensors, actuators, host computers, etc. There may be differences in the communication protocols and interface standards between different devices, which brings difficulties to the communication of PLCs. How to achieve efficient and stable communication between PLCs and other devices and ensure accurate data transmission is one of the problems that need to be solved to optimize the electrical performance of PLCs. In smart factories, PLCs need to communicate with various smart devices to realize intelligent management of the production process. If the communication compatibility is not good, it will lead to poor data transmission and affect the operating efficiency of the entire production system.

In summary, this study will conduct in-depth research around these key issues, and propose effective optimization strategies and solutions through theoretical analysis, experimental research, and actual case verification to improve the electrical performance of PLC and maximize industrial production efficiency.

2. Theoretical basis of the relationship between PLC electrical performance and productivity

2.1 Overview of PLC working principle and electrical performance

As the core control device of industrial automation, PLC works based on stored program control and cyclic scanning mechanism. PLC is mainly composed of central processing unit (CPU), memory, input/output (I/O) interface, power supply and other parts. CPU is the core of PLC, responsible for executing user programs and processing various data; memory is used to store system programs, user programs and data; I/O interface is the channel for PLC to exchange data with external devices; power supply provides stable working voltage for each part of PLC.

The working process of PLC can be divided into six stages: internal processing, communication processing, self-diagnosis, input sampling, user program execution and output refresh. These stages are executed repeatedly in a cycle called a scan cycle. In the internal processing stage, PLC initializes the hardware, checks the configuration of the I/O module, and sets the power failure protection range, etc. In the communication processing stage, PLC communicates with its own intelligent module with CPU and other external devices to complete data transmission and reception, respond to the programmer’s commands, update the programmer’s display content, and update the clock and special register content. In the self-diagnosis stage, the CPU detects the status of each PLC module. If an abnormality occurs, it will immediately diagnose and process it, and at the same time give a fault signal and light up the LED indicator on the CPU panel. When a fatal error occurs, the CPU is forced to STOP mode and stops executing the program. In the input sampling stage, PLC Scan all input terminals and store their status (0/1) in the input register, then close the input channel and enter the next step of the program; in the user program execution phase, data is taken from the input register and the internal component register, and the results are written to the output image register and related memory according to the logical operations and arithmetic operations in the program; in the output refresh phase, after the program execution is completed, all output relay states in the internal component register are transferred to the output latch at one time in the output stage, and are transmitted to the output end through isolation and driving the power amplifier circuit to drive the actual load.

The electrical performance of PLC directly affects its application effect in industrial automation systems. The following are some key electrical performance indicators:

1. Response speed : Response speed refers to the time required for the PLC to change from receiving an input signal to outputting a change in the signal, usually measured by the scan cycle. The shorter the scan cycle, the faster the PLC responds, and the faster it can respond to changes in the production process. In high-speed production lines, the PLC scan cycle is required to be at the millisecond or even microsecond level to ensure real-time control of the equipment and continuity of production. The response speed is affected by factors such as the CPU’s operating speed, the complexity of the program, and the number of I/O points. Using a high-performance CPU, optimizing the program structure, and reducing unnecessary I/O operations can effectively improve the PLC’s response speed.
2. Anti-interference capability : There are various interference sources in the industrial production environment, such as electromagnetic interference, power supply interference, temperature changes, humidity, etc. These interferences may affect the normal operation of the PLC, resulting in data errors, program loss of control, and even equipment damage. Therefore, the PLC must have strong anti-interference capabilities to ensure stable operation in harsh environments. PLC usually adopts a variety of anti-interference measures, such as hardware filtering, photoelectric isolation, shielding and grounding, etc. Hardware filtering can remove high-frequency noise and interference in the input signal; photoelectric isolation isolates the internal circuit of the PLC from the external circuit through an optical coupler device to prevent external interference signals from entering the PLC; shielding and grounding reduce the impact of electromagnetic interference by shielding and well grounding the PLC.
3. Reliability : Reliability refers to the ability of PLC to complete specified functions under specified conditions and within a specified time. Reliability is a crucial performance indicator of PLC in industrial applications, and is directly related to the continuity and stability of production. PLC adopts a variety of reliability design technologies, such as redundancy technology, fault diagnosis and self-recovery technology, etc. Redundancy technology includes power redundancy, CPU redundancy, I/O module redundancy, etc. When the main device fails, the backup device can automatically switch to ensure the normal operation of the system; fault diagnosis and self-recovery technology can monitor the operating status of PLC in real time. When a fault is detected, it can be diagnosed and processed in time, and take corresponding measures for self-recovery, such as automatic restart, switching to the backup program, etc.
4. Input and output points : Input and output points refer to the number of input devices and output devices that the PLC can connect to, usually expressed in I/O points. The more I/O points, the more devices the PLC can control, and the larger the applicable control scale. When selecting a PLC, it is necessary to determine the required I/O points based on the actual control needs to ensure that the PLC can meet the control requirements of the production system. At the same time, it is also necessary to consider the expansion capacity of the I/O points so that the I/O points can be easily increased when the production scale is expanded or the process is improved in the future.
5. Storage capacity : Storage capacity refers to the size of the memory used by the PLC to store user programs, data, and system information. The larger the storage capacity, the more programs and data the PLC can store, and the more complex control functions it can achieve. With the improvement of industrial automation, the amount of data and control logic in the production process are becoming more and more complex, and the storage capacity requirements of the PLC are also increasing. When selecting a PLC, you need to choose a PLC with sufficient storage capacity based on the actual application requirements, and you also need to consider the expansion capability of the storage capacity.

2.2 Productivity measurement indicators and influencing factors

Productivity is an important indicator to measure the efficiency and benefits of a production system. It reflects the ability of a production system to produce products or provide services within a certain period of time. In industrial production, the improvement of productivity means being able to produce more products in the same period of time, or consuming less resources when producing the same number of products. For industrial production systems controlled by PLC, the measurement indicators of productivity mainly include the following aspects:

1. Output : Output is the most intuitive indicator of productivity, which indicates the number of products produced by a production system within a certain period of time. On the automated production line, PLC achieves continuity and efficiency of the production process by precisely controlling the operation of the equipment, thereby increasing the output of the product. The production line of an automobile manufacturer can produce dozens of cars per hour by controlling the actions of robots and automated equipment through PLC, which greatly increases the output compared to traditional manual production methods.
2. Production efficiency : Production efficiency refers to the amount of work completed by the production system per unit time, usually expressed as the ratio of production time to output. The higher the production efficiency, the greater the amount of work completed by the production system per unit time, and the higher the productivity. In the chemical production process, PLC keeps the production process in the best state by real-time monitoring and adjusting various process parameters, thereby improving production efficiency. By optimizing the PLC control program, the number of equipment starts and stops and the waiting time in the production process are reduced, and the production efficiency is increased by 20%.
3. Equipment utilization rate : Equipment utilization rate refers to the ratio of the actual equipment operation time to the planned operation time, which reflects the efficiency of equipment use. In industrial production, improving equipment utilization rate can give full play to the production capacity of equipment, reduce equipment idle time, and thus improve productivity. PLC can timely detect equipment failures and carry out repairs through real-time monitoring and fault diagnosis of equipment, ensure the normal operation of equipment, and improve equipment utilization rate. Through the PLC monitoring system, potential equipment failures were discovered in time and repaired in advance, which increased the equipment utilization rate from the original 80% to 90%.
4. Product quality : Product quality is one of the important indicators to measure productivity, which directly affects the market competitiveness of products and the economic benefits of enterprises. In the production process, PLC ensures the stability and consistency of product quality by accurately controlling various process parameters. In electronic manufacturing enterprises, the automated production line controlled by PLC can accurately control the welding temperature, welding time and other parameters of electronic products, ensuring the welding quality of electronic products and improving the qualified rate of products.
5. Production cycle : The production cycle refers to the time required from raw material input to product output, which reflects the production speed of the production system. Shortening the production cycle can improve production efficiency, speed up capital turnover, and thus improve productivity. PLC shortens the production cycle by optimizing the production process and controlling the operating speed of equipment. In clothing manufacturing companies, PLC-controlled automated cutting and sewing equipment has shortened the production cycle of clothing from one week to three days.

There are many factors that affect productivity. For industrial production systems controlled by PLC, the following are some of the main factors:

• Equipment operation efficiency : Equipment operation efficiency is one of the key factors affecting productivity. PLC can reduce equipment downtime and improve equipment operation efficiency by precisely controlling equipment operation. On an automated production line, PLC can automatically adjust the equipment’s operating speed and working mode according to production needs to ensure that the equipment is always in the best operating state. At the same time, PLC can also monitor and diagnose equipment in real time, detect and solve equipment failures in a timely manner, and avoid long-term equipment downtime, thereby improving equipment operation efficiency.
• Product quality : Product quality directly affects the market competitiveness of products and the economic benefits of enterprises. In the production process, PLC ensures the stability and consistency of product quality by accurately controlling various process parameters. If the product quality is unstable, it will lead to a decrease in product qualification rate, increase production costs, and also affect the reputation and market share of the enterprise. Therefore, improving product quality is one of the important ways to improve productivity.
• Production process optimization : Optimization of production processes can improve production efficiency, reduce production costs, and thus increase productivity. PLC can identify bottlenecks and irrationalities in the production process through real-time monitoring and data analysis of the production process, and optimize and improve it. By optimizing the production process, the waiting time and material handling distance in the production process are reduced, and production efficiency is improved.
• Personnel quality : The skill level and work attitude of operators also have a great impact on productivity. Operators who are proficient in PLC programming and operation skills can better play the control advantages of PLC and improve production efficiency and product quality. At the same time, the operator’s work attitude is proactive, conscientious and responsible, which can also reduce the impact of human factors on production and improve productivity.
• External environmental factors : External environmental factors such as raw material supply, market demand, policies and regulations will also have an impact on productivity. Unstable raw material supply will lead to production interruptions and affect production efficiency; changes in market demand will affect product sales, thereby affecting the company’s production plan and productivity; adjustments to policies and regulations will also have an impact on the company’s production and operation, and thus affect productivity.

2.3 The impact of PLC electrical performance on productivity

There is a close intrinsic connection between the electrical performance of PLC and productivity. It affects production efficiency, product quality and equipment stability in many aspects, which in turn has a significant impact on productivity.

2.3.1 Impact on production efficiency

The response speed of PLC is one of the key factors affecting production efficiency. On a high-speed production line, each link of the production process is closely connected, and any delay in any link may cause the entire production line to stagnate. The rapid response capability of PLC can ensure that the equipment executes various control instructions in a timely manner and reduce the waiting time in the production process. In the stamping production line of automobile manufacturing, PLC needs to quickly control the action of the stamping machine so that it can complete the stamping of the sheet in a short time. If the response speed of PLC is too slow, it will cause the action of the stamping machine to be delayed, thereby affecting production efficiency. According to relevant research, when the scanning cycle of PLC is shortened from 10ms to 5ms, the production efficiency of the production line can be increased by 10% – 20%.

The data processing capability of PLC also has an important impact on production efficiency. With the development of digitalization and intelligence of industrial production, the amount of data generated in the production process is increasing, and these data need to be processed and analyzed by PLC in real time. Powerful data processing capabilities enable PLC to quickly process a large amount of production data, provide accurate basis for production decisions, thereby optimizing production processes and improving production efficiency. In the chemical production process, PLC needs to process temperature, pressure, flow and other data collected by various sensors in real time, and adjust production parameters based on these data to ensure the stable operation of the production process. If the data processing capability of PLC is insufficient, data processing will be untimely, affecting the adjustment of production parameters and thus reducing production efficiency.

2.3.2 Impact on product quality

The high-precision control capability of PLC is the key to ensuring product quality. In the production process, product quality is often affected by many factors, such as fluctuations in process parameters such as temperature, pressure, and speed. PLC accurately controls these process parameters to keep them within the specified range, thereby ensuring the stability and consistency of product quality. In electronic manufacturing companies, the chip manufacturing process has very strict requirements on process parameters. PLC ensures the manufacturing accuracy and quality of chips by accurately controlling the parameters of process links such as lithography and etching. According to statistics, the qualified rate of products can be increased by 5% – 10% by using a production system controlled by PLC.

The reliability and stability of PLC also have an important impact on product quality. If PLC fails during the production process, it may cause the production process to be interrupted or produce unqualified products. Therefore, improving the reliability and stability of PLC can reduce product quality problems caused by equipment failure and ensure the stability of product quality. In the pharmaceutical industry, the production process of drugs has extremely high requirements for the reliability and stability of equipment. Any failure of PLC may cause unqualified drug quality and even harm the health of patients. By adopting redundancy technology, fault diagnosis and self-recovery technology and other measures, the reliability and stability of PLC are improved, thereby ensuring the production quality of drugs.

2.3.3 Impact on equipment stability

The anti-interference ability of PLC is an important factor to ensure the stable operation of equipment. In industrial production environments, there are various electromagnetic interference, power supply interference and other factors, which may affect the normal operation of PLC and cause unstable operation of equipment. PLC effectively reduces the impact of interference on equipment and ensures the stable operation of equipment by adopting anti-interference measures such as hardware filtering, photoelectric isolation, and shielding grounding. In the power system, PLC is used to control the equipment of substations. Due to the strong electromagnetic interference in the power system, the anti-interference ability of PLC is very high. By adopting high-performance anti-interference measures, PLC can operate stably in a strong electromagnetic interference environment, ensuring the normal operation of substation equipment.

The reliability design of PLC also has an important impact on the stability of the equipment. By adopting reliability designs such as redundancy technology, fault diagnosis and self-recovery technology, PLC can maintain the normal operation of the system when some hardware fails, thereby improving the stability of the equipment. In the field of aerospace, the control system of the aircraft adopts redundant PLC. When the main PLC fails, the backup PLC can automatically switch to ensure the flight safety of the aircraft. According to research, the control system using redundant PLC can increase the mean time between failures of the equipment by several times, greatly improving the stability of the equipment.

3. Analysis of factors affecting PLC electrical performance

3.1 Hardware Factors

3.1.1 Processor Performance

As the core component of PLC, the performance of the processor plays a decisive role in the electrical performance of PLC. The computing speed of the processor determines the efficiency of PLC processing input signals and the speed of executing user programs. On high-speed production lines, such as stamping production lines for automotive parts, each stamping action requires the PLC to respond quickly and accurately control the operation of the stamping machine. If the processor computing speed is insufficient, the time interval from the sensor detecting the plate arrival signal to controlling the stamping machine action will be extended, resulting in a slower production line beat and reduced production efficiency. When the processor computing speed is doubled, the production efficiency of the stamping production line can be increased by 30% – 40%.

Storage capacity is also one of the important indicators of processor performance. With the development of digitalization and intelligence of industrial production, the amount of data generated in the production process has increased dramatically, and PLC is required to store a large amount of production data, user programs and system configuration information. Sufficient storage capacity can ensure the normal operation of PLC and avoid data loss or abnormal program operation due to insufficient storage space. In large chemical companies, PLC needs to store and process various process parameters, equipment operation status and other data in real time. If the storage capacity is insufficient, key data may not be recorded, affecting the monitoring and analysis of the production process, and may even cause production accidents.

In addition, the processor’s instruction set architecture and cache mechanism will also affect the electrical performance of the PLC. Advanced instruction set architecture can improve the execution efficiency of instructions and reduce the execution time of instructions; and efficient cache mechanism can quickly read and store data, reduce the data transmission delay between the processor and memory, and thus improve the overall performance of the PLC. For example, the instruction set architecture using pipeline technology can enable the processor to process multiple instructions at the same time, greatly improving the operation speed; large-capacity cache can reduce the number of times the processor accesses the memory and improve the efficiency of data processing.

3.1.2 Power Quality

The power supply is the basis for the normal operation of the PLC, and its quality has an important impact on the electrical performance of the PLC. The stability of the power supply is directly related to the reliability of the PLC. In an industrial production environment, the grid voltage may fluctuate, surge, and other abnormal conditions. When the voltage fluctuation exceeds the normal operating range of the PLC, it may cause the internal circuit of the PLC to work abnormally, resulting in data errors, program loss of control, and other problems. In areas with unstable power supply, the PLC control system may frequently fail, affecting the normal production.

The anti-interference ability of the power supply is also a key factor affecting the electrical performance of the PLC. There are various sources of electromagnetic interference in industrial sites, such as the start and stop of high-power motors, the operation of electric welders, etc. These interferences may be transmitted to the inside of the PLC through the power supply line, affecting its normal operation. If the anti-interference ability of the power supply is insufficient and these interference signals cannot be effectively filtered out, the control accuracy of the PLC will be reduced, and even equipment failure will be caused. In order to improve the anti-interference ability of the power supply, filters, isolation transformers and other equipment are usually installed at the power input end to reduce the impact of interference signals on the PLC.

In addition, the ripple factor of the power supply cannot be ignored. Ripple refers to the AC component in the power supply output voltage. Excessive ripple will interfere with the digital and analog circuits of the PLC and affect its performance. In situations where high control accuracy is required, such as electronic chip manufacturing production lines, low-ripple power supplies are required to ensure that the PLC can accurately control various parameters in the production process and ensure product quality.

3.1.3 Input and output module characteristics

The input and output module is the bridge for data exchange between PLC and external devices, and its characteristics have a direct impact on the electrical performance of PLC. The response speed of the input and output module determines the timeliness of PLC’s perception and control of external signals. In high-speed motion control systems, such as robot motion control, PLC needs to quickly collect sensor position signals and control the operation of the motor in a timely manner. If the response speed of the input and output module is too slow, it will cause the robot’s action to be delayed, affecting the accuracy and stability of the motion. When the response speed of the input and output module is increased by 50%, the robot’s motion control accuracy can be improved by 20% – 30%.

The accuracy of the input and output modules is crucial for some application scenarios that require high control accuracy. In industrial automation production, many process steps require precise control of parameters such as temperature, pressure, and flow. If the accuracy of the input and output modules is insufficient, there will be a deviation between the actual control value and the set value, affecting product quality. In chemical production, the temperature control accuracy in the reactor is extremely high. If the temperature measurement accuracy error of the input and output modules is too large, it may cause the chemical reaction to get out of control and cause a safety accident.

In addition, the anti-interference ability of the input and output modules cannot be ignored. In industrial sites, input and output modules are easily affected by electromagnetic interference, electrostatic interference, etc., resulting in signal transmission errors. In order to improve the anti-interference ability of input and output modules, optoelectronic isolation, shielding and grounding are usually used to ensure reliable signal transmission. For example, optoelectronic isolation technology isolates the input and output modules from the external circuit through optocouplers, effectively preventing the intrusion of external interference signals; shielding and grounding reduce the impact of electromagnetic interference by shielding and well grounding the input and output cables.

3.2 Software Factors

3.2.1 Programming Algorithm and Logic Optimization

The design of programming algorithms and logic has a significant impact on the electrical performance of the PLC, especially in terms of scan cycles and resource utilization. Different programming algorithms have different execution efficiency and resource consumption when processing the same task. In sequential control programming, structured programming methods are used to decompose complex control tasks into multiple functional modules. Each module implements specific functions. Through reasonable module calls and logical combinations, the readability and readability of the program can be improved. Maintainability, while reducing the execution time of the program and shortening the scan cycle. In the PLC control system of an automated production line, the functions of material transportation, processing, and detection are written as independent modules, and these modules are called in sequence through the main program to realize the automated operation of the production line. Compared with traditional linear programming, structured programming shortens the scan cycle by 20% – 30% and improves production efficiency.

In terms of conditional judgment and loop control, optimizing programming logic can also effectively improve the performance of PLC. In complex production process control, it is necessary to judge based on multiple conditions to determine the operating status of the equipment. Reasonable use of conditional judgment statements and avoiding unnecessary conditional nesting and repeated judgment can reduce the execution time of the program. In a temperature control system, according to the feedback signal of the temperature sensor, it is necessary to judge whether the temperature reaches the set value and the temperature change trend, so as to control the start and stop of the heating equipment. By optimizing the conditional judgment logic, integrating and simplifying the relevant conditions, the execution efficiency of the program is improved by 15% – 20%, ensuring the accuracy and timeliness of temperature control.

Loop control is often used in PLC programming to handle repetitive tasks, such as data collection and processing. Optimizing the loop control algorithm and setting the loop conditions and number of loops reasonably can reduce unnecessary loop execution and improve resource utilization. In a data acquisition system, it is necessary to periodically collect data from multiple sensors. By optimizing the loop control algorithm and using timed interrupts to trigger data acquisition, unnecessary loop waiting is avoided, which improves the efficiency of data acquisition by 30% – 40%, while reducing the CPU resource consumption of the PLC.

3.2.2 Compatibility and stability of system software

As the core support for PLC operation, the compatibility of system software with hardware and its own stability are crucial to the electrical performance of PLC. When the system software is incompatible with the hardware, it may cause problems such as the inability of the device to communicate normally, data transmission errors or system crashes. During the upgrade of the PLC control system, if the newly installed system software does not match the original hardware equipment, communication interruptions and I/O module failures may occur, seriously affecting the normal production. In an automation transformation project of a certain factory, the system software of the PLC was upgraded, but the compatibility of the software and hardware was not fully considered, resulting in frequent failures of the production line during operation and a significant drop in production efficiency. After re-debugging and matching the system software and hardware, the compatibility problem was solved and the normal operation of the production line was restored.

The stability of the system software itself is also directly related to the electrical performance of the PLC. Unstable system software may have problems such as memory leaks and abnormal program termination, which will affect the normal operation of the PLC. Memory leaks will cause the system memory to gradually decrease, and eventually the PLC will not be able to work properly due to insufficient memory; abnormal program termination will cause the production process to be interrupted, resulting in production losses. In order to improve the stability of the system software, software developers usually carry out a lot of testing and optimization work to fix loopholes and defects in the software. At the same time, users should also update the system software in time during use to obtain the latest stability and performance optimization. In some industrial fields with extremely high reliability requirements, such as aerospace, power systems, etc., the system software of the PLC must undergo rigorous testing and verification to ensure its stability and reliability to ensure the safety and stability of the production process.

3.3 External environmental factors

3.3.1 Electromagnetic Interference

Electromagnetic interference is one of the important external environmental factors that affect the electrical performance of PLC. Its sources are wide and its transmission paths are complex. In industrial production sites, electromagnetic interference mainly comes from the following aspects:

1. Power system : Various electrical equipment in the power system, such as transformers, high-voltage transmission lines, high-power motors, etc., will generate strong electromagnetic fields during operation. When the intensity of these electromagnetic fields exceeds a certain threshold, they will interfere with nearby PLCs. In steel mills, large steelmaking electric furnaces will generate drastic current changes during operation, causing strong electromagnetic radiation, which may cause data errors or control anomalies in nearby PLC control systems.
2. Communication equipment : Wireless communication equipment widely used in modern industrial production, such as mobile phone base stations, wireless walkie-talkies, WiFi devices, etc., can also generate electromagnetic interference. These communication devices emit high-frequency electromagnetic waves when working. If the working frequency is close to that of the PLC, it may interfere with the communication and data processing of the PLC. In some intelligent factories, a large number of wireless sensors and actuators communicate with the PLC through wireless networks. If there are strong wireless communication interference sources around, it may cause communication interruption or data transmission errors.
3. Other electrical equipment : Electric welding machines, fluorescent lamps, variable frequency speed regulators and other electrical equipment will also generate electromagnetic interference when working. Electric welding machines will generate high-frequency pulse currents during welding, which will radiate electromagnetic waves to the surrounding space and interfere with nearby PLCs; fluorescent lamps will generate high-frequency oscillations when starting and working, which will also cause certain interference to PLCs; variable frequency speed regulators adjust the motor speed by changing the power supply frequency, and will generate a large number of harmonics during their operation, which will interfere with PLCs through power supply lines and space radiation.

Electromagnetic interference affects the electrical performance of PLC mainly through two ways: conduction and radiation:

• Conducted interference : Conducted interference refers to electromagnetic interference that is transmitted to the inside of the PLC through conductors such as power lines and signal lines. In industrial production, interference signals in the power grid can enter the PLC through the power line of the PLC, affecting its normal operation. When there are interferences such as voltage surges and harmonics in the power grid, these interference signals will be transmitted to the power module of the PLC through the power line, thereby affecting other parts of the PLC. Interference on the signal line will also affect the input and output signals of the PLC, causing signal distortion or errors. If the signal line between the sensor and the PLC is subject to electromagnetic interference, the signal output by the sensor may be interfered during the transmission process, causing the PLC to receive incorrect signals and make incorrect control decisions.
• Radiated interference : Radiated interference refers to electromagnetic interference that propagates into the PLC through space radiation. When the PLC is in a strong electromagnetic radiation environment, the radiated interference will directly act on the circuit components of the PLC, affecting its normal operation. Near large substations, due to the presence of strong electromagnetic fields, the surrounding PLCs may be affected by radiation interference, resulting in abnormal program operation or data loss. Radiated interference may also affect the PLC’s communication network, causing interference to the communication signal, resulting in communication interruption or data transmission errors.

In order to reduce the impact of electromagnetic interference on the electrical performance of PLC, the following measures are usually taken:

• Shielding : Shield the PLC and its related equipment to reduce the radiation and reception of electromagnetic interference. Metal shielding shells, shielding cables, etc. can be used to isolate the PLC from external electromagnetic interference sources. The metal shielding shell can block the entry of external electromagnetic fields and protect the internal circuit of the PLC from interference; the shielding cable can effectively reduce the electromagnetic interference on the signal line and ensure the reliable transmission of the signal.
• Filtering : Install filters on the power supply line and signal line to filter out interference signals. The power supply filter can remove high-frequency noise and interference in the power supply to ensure the stability of the PLC power supply; the signal filter can filter the input and output signals, remove interference components in the signals, and improve the signal quality.
• Grounding : Good grounding is an important measure to reduce electromagnetic interference. By grounding the metal shell, shielding layer, etc. of the PLC, interference current can be introduced into the ground to avoid interference signals from affecting the inside of the PLC. At the same time, reasonable grounding layout and grounding resistance control are also very important to ensure the effectiveness of grounding.
• Reasonable wiring : During the wiring process of the PLC control system, the positions of power lines, signal lines and control lines should be reasonably arranged to avoid them interfering with each other. Route power lines and signal lines separately to reduce interference from the power lines to signal lines; avoid signal lines that are too long to reduce interference during signal transmission.

3.3.2 Environmental conditions such as temperature and humidity

Environmental conditions such as temperature and humidity have a significant impact on the electrical performance of PLC. In an industrial production environment, changes in these factors are complex and require sufficient attention.

Temperature is one of the key environmental factors that affect the electrical performance of PLC. The performance of electronic components inside the PLC will change at different temperatures, thus affecting the overall performance of the PLC. When the ambient temperature is too high, the temperature of the electronic components inside the PLC will rise due to poor heat dissipation, causing the parameters of the components to drift, such as changes in resistance and capacitance values, which in turn affects the normal operation of the circuit. Excessive temperature may also shorten the life of electronic components or even damage them. In a high temperature environment, the leakage current of the chip will increase, the power consumption will increase, and more heat will be generated, forming a vicious cycle, which may eventually cause the chip to burn out. According to research, for every 10°C increase in the temperature of electronic components, their life may be shortened by about 50%. In some high-temperature industrial production scenarios, such as steel smelting and glass manufacturing, the ambient temperature often exceeds the normal operating temperature range of the PLC. If effective heat dissipation measures are not taken, the reliability and stability of the PLC will be seriously threatened.

On the contrary, when the ambient temperature is too low, the performance of the electronic components inside the PLC may degrade. For example, the capacitance of the capacitor will decrease as the temperature decreases, causing the time constant of the circuit to change, affecting the processing and transmission of the signal; the conduction characteristics of some semiconductor devices will also be affected by temperature, which may cause logic errors or control abnormalities. In industrial production in cold areas, such as outdoor chemical production equipment in winter, the PLC may face the challenge of low temperature environment, and insulation measures need to be taken to ensure its normal operation.

The impact of humidity on the electrical performance of PLCs cannot be ignored. Excessive humidity can cause moisture to be absorbed by the surface of the circuit board inside the PLC, reducing the insulation performance of the circuit board and increasing the risk of short circuits and leakage. When there is moisture on the surface of the circuit board, it may cause problems with the electrical connection between electronic components and cause failures. In a humid environment, metal parts are prone to rust and corrosion, affecting the mechanical structure and electrical performance of the PLC. If the PLC’s shell or internal metal connectors are rusted, it may cause poor contact, affecting signal transmission and the normal operation of the equipment.

In addition, humidity may also cause chemical corrosion to the electronic components inside the PLC, further reducing the performance and life of the components. For example, some corrosive gases containing water, such as hydrogen sulfide and chlorine, are more likely to react chemically with electronic components in a high humidity environment, causing component damage. In some chemical companies or industrial production environments in coastal areas, the impact of humidity and corrosive gases is more serious, and special protective measures need to be taken, such as using moisture-proof and anti-corrosion housings and circuit board coatings to protect PLCs from humidity and corrosive gases.

In order to reduce the impact of environmental conditions such as temperature and humidity on the electrical performance of PLC, the following measures are usually taken:

1. Temperature control : To provide a suitable working temperature environment for the PLC, the ambient temperature can be controlled by installing heat dissipation devices, air conditioners and other equipment. In a high temperature environment, use heat dissipation devices such as radiators and fans to dissipate the heat generated inside the PLC to ensure that the temperature of the electronic components is within the normal range; in a low temperature environment, use heating devices or insulation materials to maintain the working temperature of the PLC. In some large industrial control systems, air conditioning systems are installed specifically for PLC control cabinets to accurately control the temperature inside the cabinet and ensure the stable operation of the PLC.
2. Humidity control : Use dehumidification equipment or desiccant to reduce the ambient humidity and keep the inside of the PLC dry. In a high humidity environment, install a dehumidifier to remove moisture from the air and reduce humidity; place desiccant in the PLC control cabinet to absorb moisture in the cabinet and prevent the circuit board from getting wet. At the same time, the PLC shell and circuit board can also be treated with moisture-proof treatment, such as using moisture-proof paint, sealant, etc., to improve its moisture-proof performance.
3. Protective measures : Protective design should be carried out for PLC, such as using sealed shells and waterproof breathable valves to prevent moisture and dust from entering the PLC. The sealed shell can effectively block external moisture and dust and protect the electronic components inside the PLC; the waterproof breathable valve can balance the internal and external air pressure while ensuring the sealing of the shell, and prevent moisture and dust from entering due to changes in air pressure. In addition, special treatment can be carried out on the electronic components inside the PLC, such as spraying with three-proof paint (moisture-proof, mildew-proof, and salt spray-proof) to improve its ability to resist environmental influences.

4. Methods and technologies for optimizing PLC electrical performance

4.1 Hardware Optimization Strategy

4.1.1 Select high-performance processors and hardware upgrades

In modern industrial automation systems, with the continuous expansion of production scale and the increasing complexity of production processes, the performance requirements for PLC are also getting higher and higher. Choosing a high-performance processor is one of the key measures to improve the electrical performance of PLC. High-performance processors have higher computing speed and more powerful data processing capabilities, which can significantly shorten the PLC scan cycle, allowing it to respond to external signals faster and achieve precise control of the production process. In high-speed automated production lines, such as stamping and welding production lines in automobile manufacturing, the production rhythm is tight and the equipment moves frequently, which requires extremely high response speed of PLC. Using a processor with fast computing speed and strong processing power, the PLC can complete the processing of large amounts of data and the execution of instructions in a short time, ensuring the efficient and stable operation of the production line. According to actual case analysis, in a stamping production line of an automobile manufacturing company, after upgrading the original PLC processor to a high-performance processor, the production efficiency of the production line increased by 20%, and the product qualification rate increased by 10%.

When choosing a processor, you need to consider several key factors. The first is the core architecture of the processor. Different architectures differ in terms of computing speed, power consumption, and instruction set. For example, an advanced multi-core architecture processor can process multiple tasks in parallel, effectively improving computing efficiency. The second is the clock frequency of the processor. A higher clock frequency can speed up the execution of instructions, but it will also increase power consumption and heat dissipation requirements. In addition, cache size is also an important indicator. A larger cache can reduce the number of times the processor accesses memory and increase data reading and processing speed. In the production control system of a chemical company, a high-performance processor with a large cache was selected, which increased the data processing speed of the PLC by 30% when processing a large amount of process data, and the system responded more quickly.

In addition to the processor, hardware upgrades also involve other key hardware components. Memory is an important component for storing programs and data, and its capacity and read and write speed have a significant impact on the performance of PLC. Increasing the memory capacity allows the PLC to store more programs and data, avoiding abnormal program operation due to insufficient memory. At the same time, the use of high-speed memory can speed up data reading and writing and improve the overall performance of the system. In an automated production line of an electronics manufacturing company, after doubling the memory capacity of the PLC and replacing it with high-speed memory, the system’s operational stability has been greatly improved, and the problem of data processing delays in the production process has been effectively solved.

The input/output (I/O) module is the bridge between the PLC and external devices, and its performance directly affects the PLC’s ability to collect and control external signals. When upgrading the I/O module, you should choose products with fast response speed and high precision. For high-speed motion control scenarios, such as robot motion control, high-speed response I/O modules are required to ensure that the PLC can collect signals from position sensors in a timely manner and accurately control the movement of the motor. In the assembly production line of a robot manufacturer, high-precision, high-speed response I/O modules are used, which improves the robot’s motion control accuracy by 15% and assembly efficiency by 18%.

When upgrading hardware, compatibility and stability issues must be fully considered. New hardware components should be compatible with other components of the existing system to avoid hardware conflicts or mismatches. Before upgrading, a comprehensive assessment of the existing system is required to understand the model, specifications, and interface type of each hardware component to ensure that the new hardware can be seamlessly connected. At the same time, the upgraded system must be strictly tested and debugged, including functional testing, performance testing, and stability testing, to ensure that the system can operate stably and reliably under various working conditions. In an automation upgrade project of a steel enterprise, due to the failure to fully consider compatibility issues during the hardware upgrade process, communication failures occurred between the newly installed I/O module and the PLC host. After multiple debugging and hardware replacement, the problem was solved, which caused certain economic losses to the enterprise. Therefore, in the process of hardware upgrade, compatibility and stability considerations are crucial. Only by ensuring good compatibility and stability between the new hardware and the existing system can the expected effect of hardware upgrade be achieved and the electrical performance of PLC be improved.

4.1.2 Power management and anti-interference measures

As the basis for the normal operation of PLC, the stability and quality of power supply have a vital impact on the electrical performance of PLC. In industrial production environments, grid voltage fluctuations, surges, and power noise are common, which may cause PLC to work abnormally or even damage the equipment. Therefore, effective power management and anti-interference measures are the key to ensure the stable operation of PLC.

Voltage stabilization and filtering are important means of power management. The voltage stabilization device can ensure the stability of the power supply output voltage and keep it constant within a certain range. In industrial production, the grid voltage may fluctuate due to load changes, power system failures, etc., exceeding the normal working voltage range of the PLC. The use of stabilized power supplies, such as linear stabilized power supplies, switching stabilized power supplies, etc., can effectively suppress voltage fluctuations and provide a stable working voltage for the PLC. The linear stabilized power supply stabilizes the output voltage by adjusting the conduction degree of the transistor. It has the advantages of stable output voltage and small ripple, but the efficiency is relatively low; the switching stabilized power supply adjusts the output voltage through a high-frequency switching circuit, with high efficiency, but relatively large ripple. In occasions with high requirements for power supply stability, such as precision instrument control, electronic chip manufacturing, etc., linear stabilized power supplies can be selected; in occasions with high requirements for efficiency, such as large industrial equipment control, switching stabilized power supplies can be selected.

The filter circuit is used to remove high-frequency noise and interference signals in the power supply to ensure the purity of the power supply. Common filter circuits include capacitor filtering, inductor filtering and LC filtering. Capacitive filtering uses the charging and discharging characteristics of the capacitor to bypass the high-frequency noise in the power supply to the ground, thereby achieving the purpose of filtering; inductive filtering uses the impeding effect of the inductor on current changes to smooth the power supply current and reduce current fluctuations; LC filtering is The combination of capacitors and inductors combines the advantages of both and can more effectively filter out high-frequency and low-frequency noise in the power supply. In the PLC control system of a chemical enterprise, an LC filter circuit is installed at the power input end, which effectively removes harmonics and high-frequency noise in the power supply, significantly improves the working stability of the PLC and reduces the risk of power interference. equipment failure.

Anti-interference measures are an important means to ensure the normal operation of PLC in complex industrial environments. Shielding technology isolates PLC from external electromagnetic interference sources by using metal shielding shells, shielding cables, etc., reducing the radiation and reception of electromagnetic interference. The metal shielding shell can block the entry of external electromagnetic fields and protect the internal circuits of the PLC from interference; the shielding cable can effectively reduce the electromagnetic interference on the signal line and ensure the reliable transmission of the signal. In the monitoring system of a certain power substation, the PLC uses a full metal shielding shell and uses shielded cables to connect sensors and actuators, which effectively resists the influence of strong electromagnetic interference in the substation and ensures the stable operation of the system.

Grounding is one of the important measures to reduce electromagnetic interference. Good grounding can introduce interference current into the earth and prevent interference signals from affecting the PLC. The PLC control system should use an independent grounding system and ensure that the grounding resistance is less than the specified value, which is generally required to be less than 10 ohms. At the same time, attention should be paid to the grounding method and layout to avoid grounding loops and ground potential differences and prevent the introduction of new interference. In the automated production line of a certain automobile manufacturing plant, by optimizing the PLC grounding system, adopting a single-point grounding method, and reasonably arranging the grounding lines, the impact of electromagnetic interference on the PLC was effectively reduced, and the operating efficiency and stability of the production line were improved.

In addition, isolation technologies such as photoelectric isolation and transformer isolation can be used to isolate PLC from external devices to prevent external interference signals from entering PLC through electrical connections. Photoelectric isolation uses optocouplers to isolate input and output signals to achieve electrical isolation, effectively preventing the intrusion of interference signals; transformer isolation isolates input and output signals through transformers, and can also play a role in voltage conversion and impedance matching. On an automated assembly line, photoelectric isolators are used to isolate the input and output signals of PLC, which effectively improves the system’s anti-interference ability and reduces false operations caused by signal interference. By comprehensively using power management and anti-interference measures such as voltage stabilization, filtering, shielding, grounding and isolation, the electrical performance of PLC can be effectively improved to ensure its stable and reliable operation in complex industrial environments.

4.2 Software Optimization Technology

4.2.1 Advanced Programming Technology and Algorithm Application

In the field of PLC programming, the application of advanced programming technology and algorithms plays a key role in improving system performance and control effects. As an important programming concept, structured programming decomposes complex program logic into multiple modules with clear functions and independent of each other, and each module focuses on achieving specific tasks. This modular design method makes the program structure clear, easy to understand and maintain. In the control system of a large-scale automated production line, functions such as material transportation, processing, and detection can be encapsulated in different modules. The material transportation module is responsible for controlling the start and stop of the conveyor belt, speed adjustment, and material positioning; the processing module controls the actions of various processing equipment according to process requirements, such as stamping, welding, cutting, etc.; the detection module monitors the quality of the product in real time to determine whether the product meets the standards. Through structured programming, each module interacts with data and works together through a clear interface, which greatly improves the readability and maintainability of the program. When the process of the production line changes or a failure occurs, technicians can quickly locate the corresponding module for modification and debugging, reducing the impact on the entire system.

Object-oriented programming (OOP) is also increasingly used in PLC programming. It introduces concepts such as classes, objects, encapsulation, inheritance, and polymorphism, bringing a higher level of abstraction and stronger code reusability to PLC programming. In the control system of a smart factory, various devices can be abstracted into different classes, such as motor classes, sensor classes, valve classes, etc. Each class encapsulates the properties and operation methods of the device. The motor class can contain properties and methods such as the motor’s speed, direction, start, and stop; the sensor class can contain properties and methods such as the sensor type, measurement range, and read data. By creating objects of the class to instantiate specific devices, the inheritance mechanism can be used to reuse code and reduce the writing of duplicate code. If there are multiple types of motors that have some common properties and methods, a base class “motor” can be created, and then specific motor subclasses can be derived from the base class, such as “AC motor” and “DC motor”. The subclass can inherit the properties and methods of the base class and expand and rewrite them according to its own characteristics. Polymorphism allows the program to call the corresponding method according to the actual type of the object, which improves the flexibility and extensibility of the program. In the process of controlling the motor, whether using an AC motor or a DC motor object, you can call methods such as “start” and “stop” through a unified interface, and the system will perform corresponding operations based on the actual type of the object.

In addition to advanced programming techniques, optimization algorithms also play an important role in PLC control. As an intelligent control algorithm, fuzzy control algorithm can handle complex nonlinear systems and uncertainty problems, and is particularly suitable for control scenarios where it is difficult to establish an accurate mathematical model. In a temperature control system, the change in temperature is affected by many factors, such as ambient temperature, heating power, heat dissipation conditions, etc. It is difficult to establish an accurate mathematical model to describe the relationship between temperature and these factors. By using the fuzzy control algorithm, by defining fuzzy variables (such as temperature deviation, temperature change rate, etc.) and fuzzy rules (such as if the temperature deviation is large and the temperature change rate is small, then increase the heating power; if the temperature deviation is small and the temperature change rate is large, then reduce the heating power, etc.), PLC can flexibly adjust the control strategy according to the actual temperature measurement value and change situation to achieve accurate control of temperature. Compared with the traditional PID control algorithm, the fuzzy control algorithm can better adapt to the dynamic changes of the system and improve the accuracy and stability of control. In practical applications, the fuzzy control algorithm has achieved good control effects in chemical production, smart home, power system and other fields, effectively improving production efficiency and product quality.

Neural network algorithm is another powerful intelligent algorithm. It has the ability of self-learning, self-adaptation and pattern recognition, and can model and predict complex nonlinear systems. In industrial production, neural network algorithm can be used for fault diagnosis, quality prediction and optimization control. In equipment fault diagnosis, by collecting various operating data of the equipment, such as vibration, temperature, current, etc., as the input of the neural network, the trained neural network can learn the characteristic patterns of data in normal operation and fault state. When the equipment is actually running, the neural network analyzes and judges according to the real-time collected data, and can timely and accurately detect whether the equipment has a fault, and identify the fault type and fault location. In terms of quality prediction, the neural network can predict the quality of the product according to various parameters in the production process (such as raw material quality, process parameters, etc.), discover potential quality problems in advance, and take corresponding measures to adjust and improve, so as to improve the qualified rate of the product. In optimization control, the neural network can automatically optimize the control parameters according to the production goals and constraints, realize the optimal control of the production process, and improve production efficiency and economic benefits. The application of neural network algorithms in intelligent manufacturing, aerospace, transportation and other fields is becoming more and more extensive, providing strong support for the intelligence and automation of industrial production.

4.2.2 Software system optimization and maintenance

The optimization and maintenance of software systems is a key link to ensure the stable and efficient operation of PLCs, and is directly related to the continuity and stability of industrial production. Code optimization is an important means to improve software performance. By analyzing and improving program codes, the execution time and resource consumption of programs can be reduced, and the response speed of the system can be improved. In the process of code optimization, the logical structure of the program must first be reviewed to remove redundant codes and unnecessary calculations. In a data processing program, if there are repeated calculation steps or conditional judgments, these repeated parts can be extracted to form an independent function or module. By calling this function or module, repeated calculations can be avoided and the execution efficiency of the code can be improved. In a loop structure, if the loop condition does not change in each loop, the loop condition can be extracted outside the loop to reduce the amount of calculation inside the loop.

Algorithm optimization is also an important aspect of code optimization. For some complex computing tasks, choosing an appropriate algorithm can significantly improve computing efficiency. Among the sorting algorithms, the average time complexity of the quick sort algorithm is O (n log n), while the average time complexity of the bubble sort algorithm is O (n^2). For large-scale data sorting, the quick sort algorithm is used Sorting time can be greatly reduced. In practical applications, it is necessary to select appropriate algorithms based on specific problems and data size to improve program performance. In addition, proper use of the PLC’s instruction set and function blocks can also optimize the code. Different PLC instructions have different execution efficiencies. Understanding and skillfully using efficient instructions can reduce program execution time. Some PLCs provide specialized mathematical operation instructions and logic processing instructions that are optimized to execute faster. When writing programs, you should give priority to using these efficient instructions and avoid using inefficient instruction combinations.

Memory management is another important aspect of software system optimization. During the operation of the PLC, it is crucial to reasonably allocate and manage memory resources to avoid memory leaks and memory fragmentation, which is crucial to ensure the stability and performance of the system. Memory leak means that after the program applies for memory, it fails to release the allocated memory for some reason, resulting in a continuous reduction of memory resources, which may eventually lead to a system crash. In order to avoid memory leaks, when writing programs, make sure that all requested memory has corresponding release operations. After using dynamic memory allocation functions (such as malloc function in C language) to apply for memory, be sure to call the corresponding release function (such as free function) to release the memory when the memory is no longer used. At the same time, pay attention to the timing of memory release to avoid releasing memory too early or too late.

Memory fragmentation refers to the situation in which the memory space is divided into many small blocks due to inconsistent sizes of memory blocks during memory allocation and release. These small blocks cannot be effectively used, thus reducing memory utilization. In order to reduce the generation of memory fragmentation, appropriate memory allocation strategies can be adopted, such as fixed-size memory block allocation and memory pool technology. Fixed-size memory block allocation is to divide the memory into several fixed-size memory blocks. Each time memory is allocated, the appropriate block is selected from these fixed-size memory blocks for allocation, which can reduce the generation of memory fragmentation. Memory pool technology is to pre-allocate a large memory space as a memory pool. When the program needs to allocate memory, it obtains the memory block from the memory pool. When the memory block is no longer in use, it is put back into the memory pool instead of being released directly to the operating system. This can avoid frequent memory allocation and release operations and reduce the generation of memory fragmentation.

The maintenance strategy of the software system is crucial to ensure the long-term stable operation of the PLC. Regular software updates are one of the important measures to maintain the software system. Software vendors will continuously fix vulnerabilities and defects in the software, while adding new features and optimizing performance. By regularly updating the software, you can obtain the latest security patches and performance optimizations to improve the stability and security of the software. Before updating the software, you should make a comprehensive backup of the existing system, including program code, data, and configuration files, to prevent problems during the update process that may cause data loss or system failure. After updating the software, you should conduct a comprehensive test of the system to ensure that the new software version can operate normally and does not affect the functions and performance of the existing system.

Software backup is also an important part of software maintenance. Regularly backing up software can prevent software loss or damage caused by hardware failure, virus attack, human error, etc. Backup files should be stored in a safe and reliable location, such as external storage devices, network storage servers, etc. At the same time, backup files should be verified regularly to ensure the integrity and availability of backup files. When a system fails, the software can be restored from the backup file in time to reduce system downtime and ensure the continuity of production. When backing up software, pay attention to the frequency and content of the backup, and reasonably determine the backup time interval based on the importance of the system and the frequency of data updates. For important systems and frequently updated data, the frequency of backup should be increased to ensure data security. In addition to regularly updating and backing up software, a complete software maintenance record and documentation should be established. Software maintenance records should include information such as software update time, update content, backup time, backup location, and system failures and solutions. These records help technicians understand the operation and maintenance history of the software and discover and solve problems in a timely manner. Software documents should include software design documents, user manuals, operating guides, etc. These documents are very important for software maintenance and upgrades, and can help technicians quickly understand the functions and usage of the software and improve maintenance efficiency.

4.3 Environmental optimization measures

4.3.1 Electromagnetic shielding and grounding technology

Electromagnetic shielding and grounding technology are key means to reduce electromagnetic interference and ensure the electrical performance of PLC. In industrial automation environments, electromagnetic interference problems are relatively common and seriously affect the stable operation of PLC. Therefore, it is crucial to deeply understand and effectively apply these technologies.

Electromagnetic shielding technology is based on the principle of electromagnetic induction. It uses metal shielding materials, such as copper and aluminum, to surround the PLC and its related equipment to form a shielded space. When the external electromagnetic field acts on the shield, the surface of the shield will induce charges. These charges will generate an induced electromagnetic field opposite to the external electromagnetic field, thereby offsetting part of the influence of the external electromagnetic field and greatly reducing the electric field strength inside the shield. In an industrial site with strong electromagnetic interference, such as near a large substation, using a metal shielding shell to wrap the PLC control cabinet can effectively block the intrusion of external electromagnetic fields and ensure that the internal circuit of the PLC is not disturbed. The shielding effect is closely related to the conductivity, thickness and integrity of the shielding material. The better the conductivity of the material, such as copper, the better the shielding effect; appropriately increasing the thickness of the shielding material can also improve the shielding effect; and the integrity of the shield requires that the shield has no defects such as cracks and holes to prevent the leakage of electromagnetic interference.

Grounding technology is to connect the metal shell, shielding layer, etc. of the PLC to the earth well, so that the interference current can flow smoothly into the earth through the grounding wire, thereby avoiding the interference signal from affecting the inside of the PLC. Grounding resistance is an important indicator to measure the grounding effect. Generally, the grounding resistance is required to be less than 10 ohms. In situations where electromagnetic compatibility is required to be high, the grounding resistance should be less than 1 ohm. In practical applications, the PLC control system should adopt an independent grounding system to avoid sharing grounding with other equipment to prevent ground potential differences and ground loop currents. The choice of grounding method is also critical. Common grounding methods include single-point grounding, multi-point grounding, and mixed grounding. Single-point grounding is suitable for low-frequency circuits and can effectively avoid interference from ground loop currents; multi-point grounding is suitable for high-frequency circuits and can reduce ground impedance and improve grounding effects; mixed grounding combines the advantages of single-point grounding and multi-point grounding, and selects appropriate grounding methods according to different circuit characteristics. In a PLC control system that includes analog circuits and digital circuits, the analog circuit part can use single-point grounding to reduce interference to the analog signal; the digital circuit part uses multi-point grounding to improve the transmission stability of digital signals.

In practical applications, electromagnetic shielding and grounding technology often need to be used in combination to achieve the best anti-interference effect. In a large-scale automated production line, the PLC control cabinet uses a metal shielding shell for electromagnetic shielding, and the shielding shell is well grounded to the ground. The signal line in the control cabinet uses a shielded cable, and the shielding layer is grounded at one end to reduce electromagnetic interference during signal transmission. Through this comprehensive application, the anti-interference ability of the PLC control system is effectively improved, ensuring the stable operation of the production line. When designing electromagnetic shielding and grounding, it is also necessary to consider factors such as the actual needs of the system and the installation environment, and select appropriate parameters such as shielding materials, grounding methods, and grounding resistance to achieve the best anti-interference effect.

4.3.2 Environmental monitoring and control

In an industrial production environment, the normal operation of PLC is significantly affected by environmental factors such as temperature and humidity. Therefore, implementing effective environmental monitoring and control measures is crucial to ensure the electrical performance and stability of PLC.

Temperature sensors are commonly used devices for monitoring ambient temperature. Their working principle is based on the thermal resistance effect or thermocouple effect of materials. Thermal resistance temperature sensors use the property that the resistance value of metal conductors or semiconductor materials changes with temperature, and calculate the temperature by measuring the resistance value. Platinum resistance temperature sensors have the advantages of high precision and good stability, and are widely used in industrial temperature measurement. Thermocouple temperature sensors are based on the thermoelectric effect of two different metal conductors. When two different metal conductors form a closed loop and there is a temperature difference between the two ends, a thermoelectric potential will be generated in the loop, and the temperature is determined by measuring the thermoelectric potential. Thermocouple temperature sensors have a fast response speed and are suitable for high temperature measurement occasions. Installing a temperature sensor in the PLC control cabinet can monitor the temperature in the cabinet in real time. When the temperature exceeds the set threshold, an alarm will be issued in time to remind the operator to take corresponding cooling measures.

Humidity sensors are used to monitor environmental humidity. Common humidity sensors include capacitive, resistive, and ceramic. Capacitive humidity sensors use the property that the dielectric constant of humidity-sensitive materials changes with humidity to determine humidity by measuring capacitance. Resistive humidity sensors are based on the principle that the resistance of humidity-sensitive materials changes with humidity, and humidity is measured by measuring resistance. Ceramic humidity sensors have the advantages of fast response speed, high accuracy, and good stability, and are widely used in industrial humidity monitoring. In industrial environments with high humidity, such as food processing workshops and chemical production sites, installing humidity sensors can monitor environmental humidity in real time. When the humidity exceeds the normal working range of the PLC, dehumidification measures can be taken in time to prevent PLC failures due to humidity problems.

According to the environmental monitoring data, take corresponding control measures to ensure that the PLC works under suitable environmental conditions. Air conditioning is a common device for regulating temperature. In a high temperature environment, air conditioning can reduce the temperature inside the PLC control cabinet to ensure the normal operation of the PLC. In some large industrial plants, in order to ensure the stable operation of the PLC control system, precision air conditioning is installed specifically for the PLC control cabinet to accurately control the temperature inside the cabinet at around 25°C, effectively improving the reliability and stability of the PLC.

Dehumidifier is an important device for regulating humidity. In a high humidity environment, using a dehumidifier can reduce the moisture content in the air and keep the inside of the PLC dry. In some underground factories or industrial enterprises in coastal areas, due to the high humidity of the environment, the PLC control cabinet is equipped with a dehumidifier to control the humidity within the range of 40% – 60%, avoiding circuit board short circuits, corrosion and other faults caused by humidity problems.

In addition, other auxiliary measures can be taken, such as installing fans in the PLC control cabinet to enhance air circulation and improve heat dissipation; using desiccants to absorb moisture in the cabinet to further reduce humidity. In some small PLC control systems, by installing fans and placing desiccants in the control cabinet, the working environment of the PLC is effectively improved and the stability of the system is improved. By implementing environmental monitoring and control measures, a suitable working environment can be created for the PLC, reducing the impact of environmental factors on the electrical performance of the PLC, and ensuring the continuity and stability of industrial production.

V. Case Analysis

5.1 Case 1: PLC system optimization of an automobile manufacturing company

An automobile manufacturing company widely uses PLC control systems on its production lines to achieve automation and efficiency in the production process. However, with the continuous growth of market demand and the increasing complexity of production processes, the original PLC system gradually exposed some problems, affecting production efficiency and product quality.

Before optimization, the company’s PLC system had the following major problems: First, the response speed was slow. As the production line continued to speed up, the performance of the original PLC processor gradually failed to meet the needs of fast data processing and real-time control, resulting in delayed equipment response and unstable production rhythm. In the body welding process, due to the delay in the transmission of control instructions from the PLC to the welding robot, the control accuracy of the welding time and position decreased, affecting the welding quality of the body, resulting in problems such as cold welding and desoldering at some welding points, and the product qualification rate was only 85%.

Secondly, the system is not reliable enough. Factors such as electromagnetic interference and temperature changes in the production environment often cause PLC failures, affecting the normal operation of the production line. According to statistics, the downtime caused by PLC failures reaches more than 10 hours per month, causing a large amount of production losses.

In addition, the original PLC system had poor communication compatibility with some newly introduced equipment, making it impossible to achieve efficient collaboration between equipment, limiting the overall efficiency improvement of the production line.

In response to these problems, the company has taken a series of optimization measures. In terms of hardware, a high-performance processor was selected, whose computing speed was 50% higher than before, and the memory capacity was doubled, which effectively improved the data processing capability and response speed of the PLC. At the same time, the power module was upgraded, and a switching power supply with higher stability and anti-interference ability was adopted. A filter and an isolation transformer were installed at the power input end to reduce the impact of power supply fluctuations and interference on the PLC. In addition, some I/O modules with slow response speed and low precision were replaced, and high-speed and high-precision I/O modules were selected to improve the data exchange efficiency between the PLC and external devices.

In terms of software, the programming algorithm and logic of PLC have been fully optimized. The structured programming method is used to decompose the complex control program into multiple functional modules, which improves the readability and maintainability of the program. At the same time, advanced algorithms, such as fuzzy control algorithms, are used to optimize the control of welding process parameters. According to the real-time data during the welding process, the welding current, voltage, welding speed and other parameters are automatically adjusted to improve the stability of welding quality. In terms of communication, the communication protocol of PLC has been upgraded to enable seamless communication with the newly introduced equipment and realize the collaborative work between equipment.

After optimization, the performance of the company’s PLC system has been significantly improved. The response speed has been greatly improved, the response delay of the equipment has been shortened from the original 100ms to less than 20ms, the production rhythm has become more stable, and the production efficiency of the production line has increased by 30%. The reliability of the system has also been greatly enhanced. Downtime due to PLC failure has been reduced to less than 2 hours per month, a reduction of more than 80%, effectively ensuring the continuity of production.

In terms of product quality, due to the precise control of welding process parameters, the welding quality has been significantly improved, and the pass rate of body welding has increased from the original 85% to more than 95%. The new PLC system has good communication compatibility with other equipment, enabling efficient collaborative work between equipment and further improving the overall efficiency of the production line.

Through the analysis of the PLC system optimization case of this automobile manufacturing enterprise, it can be seen that through reasonable hardware upgrades and software optimization, the electrical performance of the PLC can be effectively improved, thereby improving production efficiency, product quality and equipment reliability, and bringing significant benefits to the enterprise. significant economic benefits and improved competitiveness.

5.2 Case 2: PLC performance improvement practice in a chemical manufacturing company

In its production process, a chemical manufacturing company widely uses PLC control systems to achieve precise control of various chemical reactions, material transportation, and equipment operations. However, with the gradual expansion of production scale and increasingly stringent process requirements, the original PLC system gradually exposed some problems, seriously affecting the stability and efficiency of production.

Before optimization, the company’s PLC system had the following prominent problems: First, the response speed was slow. In the chemical production process, various process parameters change rapidly, requiring the PLC to respond quickly and make adjustments. However, the performance of the original PLC processor was limited and it was unable to process a large amount of sensor data and control instructions in a timely manner, resulting in control lag. In the temperature control link, when the temperature in the reactor fluctuated abnormally, the PLC took a long time to make adjustments, resulting in a large temperature deviation, affecting the progress of the chemical reaction, and then leading to unstable product quality and a defective rate of up to 15%.

Second, the anti-interference ability is weak. The chemical production environment is complex, and there are a large number of electromagnetic interference sources, such as high-power motors, frequency converters, etc. The original PLC system has insufficient anti-interference measures and is often affected by electromagnetic interference, resulting in data transmission errors, control command misexecution and other problems. The equipment failure rate is high, and the downtime caused by equipment failure reaches more than 15 hours per month, causing great economic losses to the company.

Third, the system has poor scalability. With the development of the enterprise, the production process is constantly improving, and new control equipment and functions need to be added. However, the original PLC system did not fully consider scalability when it was designed, making it difficult to upgrade hardware and software, which restricted the production development of the enterprise.

In response to these problems, the company has taken a series of targeted optimization measures. In terms of hardware, the PLC processor was upgraded and a high-performance multi-core processor was selected. Its computing speed is 80% higher than before, which can quickly process a large amount of data and instructions, greatly shortening the system’s response time. At the same time, the memory capacity was increased, the speed of data storage and reading was improved, and the system can run stably. The power supply module was improved, and a switching power supply with high anti-interference ability was adopted, and it was equipped with a filter and a voltage regulator, which effectively reduced the impact of power supply interference on the PLC. In addition, the input and output modules were fully inspected and replaced, and modules with strong anti-interference ability and fast response speed were selected to improve the accuracy and stability of signal transmission.

In terms of software, the programming logic of PLC has been optimized. The structured programming method is used to decompose the complex control program into multiple functional modules, each module is responsible for a specific control task, and the readability and maintainability of the program are improved. At the same time, the control strategy is optimized using advanced algorithms, such as the use of fuzzy control algorithms to accurately control key process parameters such as temperature and pressure, and automatically adjust the control amount according to the deviation between the actual measured value and the set value to make the process parameters more stable. In temperature control, after the fuzzy control algorithm is used, the temperature deviation is controlled within ±1℃, which effectively improves product quality and reduces the defective rate to less than 5%.

In order to improve the anti-interference ability of the system, a series of hardware and software anti-interference measures have been taken. In terms of hardware, the PLC control cabinet has been fully shielded by electromagnetics, and metal shielded shells and shielded cables have been used to reduce the intrusion of electromagnetic interference. In terms of software, data verification and error correction functions have been added to perform real-time verification of input and output data. Once data errors are found, error correction is immediately performed to ensure data accuracy.

In terms of system scalability, the PLC system has been redesigned and a modular structure has been adopted to facilitate hardware and software upgrades and expansions. Sufficient I/O interfaces and communication interfaces have been reserved to facilitate the addition of new control devices and functions in the future.

After optimization, the performance of the chemical production company’s PLC system has been significantly improved. The response speed has been greatly improved, the control lag problem has been effectively solved, the control of process parameters has been more precise, the product quality has been significantly improved, and the defective rate has been reduced by more than 10 percentage points. The system’s anti-interference ability has been enhanced, and the equipment failure rate has been greatly reduced. The monthly downtime caused by equipment failure has been reduced to less than 5 hours, a reduction of more than 66%, effectively ensuring the continuity of production.

In addition, the optimized PLC system has good scalability, providing strong support for the company’s future production development. Through this PLC performance improvement practice, the company not only improved production efficiency and product quality, but also reduced production costs, enhanced market competitiveness, and achieved significant economic and social benefits.

5.3 Case comparison and experience summary

Through in-depth analysis of the above two cases, it can be clearly seen that although automobile manufacturing companies and chemical manufacturing companies are in different industries and have significant differences in production processes and equipment, they have many similarities in optimizing PLC electrical performance. place.

In terms of hardware optimization, both companies recognize the key role of high-performance processors in improving PLC performance. Automobile manufacturing companies have effectively improved data processing capabilities and response speed by selecting processors with 50% higher computing speed and doubled memory capacity; chemical manufacturing companies have adopted multi-core processors with 80% faster computing speed, greatly shortening the time required to System response time. This shows that selecting an appropriate high-performance processor based on the company’s own production needs can significantly improve the PLC’s computing speed and data processing capabilities to meet the growing production control needs.

The optimization of power modules is also a joint initiative of the two companies. The automobile manufacturer uses a switching power supply with stronger stability and anti-interference ability, and is equipped with a filter and an isolation transformer; the chemical manufacturer uses a switching power supply with high anti-interference ability, and is equipped with a filter and a voltage regulator. These measures effectively reduce the impact of power supply fluctuations and interference on PLCs, ensuring the stable operation of PLCs in complex industrial environments.

The upgrade of input and output modules is equally important. Automobile manufacturers replaced I/O modules with slow response speed and low precision with high-speed and high-precision modules; chemical manufacturers comprehensively checked and replaced input and output modules, and selected modules with strong anti-interference ability and fast response speed. This series of operations improves the data exchange efficiency between PLC and external devices, and ensures the accuracy and stability of signal transmission.

In terms of software optimization, structured programming methods are widely used in both companies. Automobile manufacturing companies decompose complex control programs into multiple functional modules, improving the readability and maintainability of the program; chemical manufacturing companies also use structured programming to decompose control programs into multiple functional modules, each module is responsible for specific control tasks. This programming method makes the program structure clearer, facilitates technicians to debug and maintain, and improves programming efficiency and program reliability.

The application of advanced algorithms has also brought significant benefits to the two companies. Automobile manufacturing companies use fuzzy control algorithms to optimize welding process parameters, improving the stability of welding quality; chemical manufacturing companies use fuzzy control algorithms to accurately control key process parameters such as temperature and pressure, effectively improving product quality. This fully demonstrates that selecting appropriate advanced algorithms based on the characteristics of the production process can achieve precise control of the production process and improve product quality and production efficiency.

In the face of their own unique problems, the two companies also took targeted measures. The automobile manufacturer focused on solving the communication compatibility problem between the system and the new equipment, and achieved seamless communication and collaborative work between the equipment by upgrading the communication protocol; the chemical production company focused on improving the anti-interference ability and scalability of the system, and effectively enhanced the anti-interference ability and scalability of the system through electromagnetic shielding processing, adding data verification and error correction functions, and adopting modular structure design.

In summary, optimizing PLC electrical performance requires comprehensive consideration of hardware, software, environment and other factors, and taking targeted optimization measures. When optimizing PLC systems, enterprises should fully draw on these successful experiences and formulate reasonable optimization plans based on their own production characteristics and needs to improve production efficiency, product quality and equipment reliability, and enhance the market competitiveness of enterprises.

6. Optimization effect evaluation and economic benefit analysis

6.1 Optimization effect evaluation indicators and methods

In order to comprehensively and accurately evaluate the effect of PLC electrical performance optimization, it is necessary to determine a series of scientific and reasonable evaluation indicators and adopt appropriate evaluation methods. These indicators and methods can intuitively reflect the impact of optimization measures on production efficiency, product quality, etc., and provide a strong basis for enterprise decision-making.

In terms of evaluation indicators, the production efficiency improvement rate is a key indicator, which directly reflects the increase in the output of the optimized production system per unit time. The production efficiency improvement rate can be calculated by the change in product output per unit time before and after optimization, and the formula is: production efficiency improvement rate = (output per unit time after optimization – output per unit time before optimization) / output per unit time before optimization × 100%. On a certain electronic product production line, 100 products were produced per hour before optimization, and 120 products were produced per hour after optimization, so the production efficiency improvement rate = (120 – 100) / 100 × 100% = 20%.

The product quality pass rate is also an important indicator to measure the optimization effect, which reflects the impact of optimization measures on the stability of product quality. The calculation method of product quality pass rate is: product quality pass rate = number of qualified products / total number of products × 100%. In a certain machinery manufacturing enterprise, the product quality pass rate was 85% before optimization, and the product quality pass rate increased to 95% after optimization, which shows that the optimization measures have effectively improved product quality.

The reduction rate of equipment failure rate should not be ignored either, as it reflects the reliability and stability of the optimized equipment. The reduction rate of equipment failure rate can be calculated by the change in the number of equipment failures before and after optimization, using the formula: Equipment failure rate reduction rate = (number of equipment failures before optimization – number of equipment failures after optimization) / number of equipment failures before optimization × 100%. In a chemical production enterprise, the number of equipment failures per month before optimization was 10 times, and after optimization, the number of equipment failures per month was reduced to 5 times, so the equipment failure rate reduction rate = (10 – 5) / 10 × 100% = 50%.

In terms of evaluation methods, the experimental method is a commonly used method. By setting up an experimental group and a control group, under the same conditions, the PLC system of the experimental group is optimized, while the control group remains unchanged, and then the performance indicators of the two groups are compared to evaluate the optimization effect. On a certain automated production line, two identical production lines were selected, one as the experimental group, and its PLC system was upgraded with hardware and software optimized; the other was used as the control group and no optimization was performed. After a period of operation, the production efficiency, product quality, and equipment failure rate of the two production lines were compared. It was found that the production efficiency of the experimental group increased by 25%, the product quality qualification rate increased by 10%, and the equipment failure rate decreased by 60%, while the indicators of the control group remained basically unchanged, thus verifying the effectiveness of the optimization measures.

The comparison method is also an effective evaluation method, which evaluates the optimization effect by comparing the performance parameters and production data of the PLC system before and after optimization. In a certain automobile manufacturing company, the response speed, data processing capacity, and production line output and quality data of the PLC system before and after optimization were compared. It was found that the response speed of the PLC system after optimization increased by 30%, the data processing capacity increased by 40%, the production line output increased by 20%, and the product quality qualification rate increased by 8%, which intuitively demonstrated the improvement of the PLC electrical performance and production efficiency by the optimization measures.

In addition to experimental and comparative methods, simulation methods can also be used, using professional software to model and simulate the PLC system, simulate different working scenarios and optimization plans, and predict the optimization effects. In a certain power control system, simulation software was used to model the PLC system, simulated different electromagnetic interference environments and optimization measures, and predicted the anti-interference ability and stability of the optimized system. It can be seen intuitively from the simulation results that after adopting electromagnetic shielding and grounding optimization measures, the anti-interference ability of the system has been significantly improved, effectively reducing the impact of electromagnetic interference on the system.

By comprehensively using these evaluation indicators and methods, the effect of PLC electrical performance optimization can be comprehensively and accurately evaluated, providing scientific basis for enterprises to further improve and optimize PLC systems.

6.2 Economic benefit analysis model and application

When evaluating the economic benefits of PLC electrical performance optimization, the cost-benefit analysis model is a common and effective tool. This model helps companies clearly understand the economic feasibility and investment value of optimization measures by quantitatively analyzing the cost input and benefit output in the optimization process.

In terms of cost, the cost of hardware upgrade is a part that cannot be ignored. Replacing high-performance processors, upgrading memory and I/O modules and other hardware equipment all require a certain amount of money. In the PLC system optimization of an electronic manufacturing company, the cost of replacing high-performance processors was 50,000 yuan, and the cost of upgrading memory and I/O modules was 30,000 yuan and 40,000 yuan respectively, and the total cost of hardware upgrade reached 120,000 yuan. Software optimization costs include software development, debugging and maintenance costs. The optimization of PLC programming algorithms, the upgrade of software systems and subsequent maintenance work all require professional technicians and corresponding time costs. In this electronic manufacturing company, the cost of software optimization was 80,000 yuan, including the labor cost of programmers, the purchase and use of software tools, etc.

Environmental optimization costs mainly involve the construction of electromagnetic shielding and grounding facilities, as well as the purchase and operation costs of environmental monitoring and control equipment. In a chemical company, in order to reduce the impact of electromagnetic interference on PLC, the cost of installing electromagnetic shielding devices and improving the grounding system is 60,000 yuan; at the same time, in order to control the ambient temperature and humidity, the cost of purchasing air conditioners, dehumidifiers and other equipment is 4 Ten thousand yuan, the annual operation and maintenance cost is 20,000 yuan.

In terms of benefits, the benefits brought by improved production efficiency are significant. By optimizing PLC electrical performance, production efficiency is improved and product output per unit time is increased, resulting in additional sales revenue. In a certain automobile manufacturing company, the production efficiency of the optimized production line has increased by 20%, and 100 more cars can be produced every month. The profit of each car is 20,000 yuan, so the additional profit brought by the improvement of production efficiency every month is 2 million yuan.

The benefits brought by the improvement of product quality are mainly reflected in the reduction of defective rate and the increase of product added value. In a machinery manufacturing enterprise, the defective rate of products was 10% before optimization, and it was reduced to 5% after optimization. 10,000 products were produced per month, and the cost of each product was 1,000 yuan. Therefore, the cost saved per month due to the reduction of defective rate was 500,000 yuan. The improvement of product quality may also make the product get higher price in the market, thereby increasing sales revenue.

The benefits brought by the reduction of equipment failure rate are mainly reflected in the reduction of equipment maintenance costs and the shortening of downtime. In a certain power company, the annual maintenance cost of equipment was 500,000 yuan before optimization, and it was reduced to 200,000 yuan after optimization; at the same time, the annual downtime of equipment was reduced from 50 hours to 20 hours, and the downtime loss per hour was 10,000 yuan. Therefore, the benefits brought by the reduction of equipment failure rate are 600,000 yuan per year.

The return on investment (ROI) model is another important economic benefit analysis tool. It evaluates the profitability and investment value of an investment project by calculating the ratio between the expected return of the investment project and the investment cost. The calculation formula of ROI is: ROI = (annual profit or average annual profit / total investment) × 100%. In a PLC system optimization project for an automated production line, the total investment is 1 million yuan, including costs for hardware upgrades, software optimization, and environmental optimization. After optimization, the additional profit brought by increased production efficiency, improved product quality, and reduced equipment failure rate is 300,000 yuan each year. Then the ROI of the project = (30 / 100) × 100% = 30%. This shows that the project has a high return on investment and a large investment value.

By applying the cost-benefit analysis model and the return on investment model, enterprises can comprehensively and accurately evaluate the economic benefits brought by PLC electrical performance optimization, providing strong support for enterprise decision-making. In actual applications, enterprises should also consider the feasibility and investment value of optimization measures in combination with their own development strategies, market demand and financial conditions, so as to maximize the economic benefits of enterprises.

6.3 Comparison of economic benefits before and after optimization of case enterprises

By making a detailed comparison of the economic benefits of the case companies before and after optimization, the remarkable results brought by the optimization of PLC electrical performance can be intuitively demonstrated. Take a certain automobile manufacturing company as an example. Before the optimization, due to problems such as slow response speed, insufficient reliability and poor communication compatibility of the PLC system, the production efficiency was low, the product quality was unstable, and the equipment failure rate was high, which brought great economic losses to the company.

In terms of production efficiency, the company’s production line produced 50 cars per hour before optimization, and increased to 65 cars after optimization, with a 30% increase in production efficiency. This means that within the same working hours, the company can produce more products, thereby increasing sales revenue. Assuming that the price of each car is 150,000 yuan, after optimization, (65 – 50) × 8 × 22 = 2,640 more cars can be produced per month (based on 22 working days and 8 hours of work per day), and the increased sales revenue is 2,640 × 15 = 396 million yuan.

In terms of product quality, the qualified rate of products before optimization was 85%, and it increased to 95% after optimization. The improvement of product quality not only reduces the losses caused by defective products, but also enhances the brand image and market competitiveness of the enterprise. Taking the production of 10,000 cars per month as an example, the number of defective products before optimization was 10,000×(1 – 85%) = 1,500, and the number of defective products after optimization was reduced to 10,000×(1 – 95%) = 500. Assuming that the processing cost of each defective product is 50,000 yuan, the defective product processing cost can be saved by (1,500 – 500)×5 = 50 million yuan per month after optimization.

In terms of equipment failure rate, before optimization, the downtime caused by PLC failure reached more than 10 hours per month. The equipment failure rate was high, which affected the continuity of production. After optimization, downtime was reduced to less than 2 hours per month, a reduction of more than 80%. Reduced equipment failure rates reduce equipment repair costs and downtime losses. Assuming that the hourly downtime loss is 100,000 yuan and the equipment maintenance cost is 200,000 yuan per month, then after optimization, the monthly downtime loss and maintenance cost can be reduced by (10 – 2) × 10 + 20 – 2 × 10 = 800,000 yuan .

Taking a chemical manufacturing company as an example, before optimization, due to problems such as slow response, weak anti-interference ability, and poor scalability of the PLC system, the product defective rate was high, the equipment failure rate was high, and the production efficiency was low. After optimization, production efficiency has been greatly improved, product defective rates have been reduced, and equipment failure rates have been significantly reduced, bringing considerable economic benefits to the enterprise.

In terms of production efficiency, the company’s daily output of chemical products was 100 tons before optimization, and increased to 120 tons after optimization, with a 20% increase in production efficiency. Assuming the profit per ton of product is 5,000 yuan, after optimization, the company can produce (120 – 100) × 30 = 600 tons more products per month (calculated as 30 days), and the increased profit is 600 × 5,000 = 3 million yuan.

In terms of product quality, the defective rate of products was 15% before optimization, and it was reduced to 5% after optimization. Taking the production of 3,000 tons of products per month as an example, the number of defective products before optimization was 3,000×15% = 450 tons, and the number of defective products after optimization was reduced to 3,000×5% = 150 tons. Assuming that the processing cost of each ton of defective products is 3,000 yuan, the defective product processing cost can be saved by (450 – 150)×3,000 = 900,000 yuan per month after optimization.

In terms of equipment failure rate, before optimization, downtime caused by equipment failure reached more than 15 hours per month, and equipment maintenance costs were high. After optimization, downtime was reduced to less than 5 hours per month, a reduction of more than 66%. Assuming that the hourly downtime loss is 80,000 yuan and the equipment maintenance cost is 300,000 yuan per month, then after optimization, the monthly downtime loss and maintenance cost can be reduced by (15 – 5) × 8 + 30 – 5 × 8 = 700,000 yuan .

Through the comparison of the economic benefits of the above two case companies before and after optimization, it can be clearly seen that optimizing PLC electrical performance can significantly improve the production efficiency of the company, improve product quality, and reduce equipment failure rates, thereby bringing huge economic benefits to the company. . These actual cases provide powerful references for other companies to optimize PLC systems, proving the importance of optimizing PLC electrical performance for companies to improve their competitiveness and achieve sustainable development.

7. Conclusion and outlook

7.1 Summary of research results

This study deeply analyzes the hardware, software and external environmental factors that affect PLC electrical performance, and proposes a series of comprehensive and effective optimization methods and technologies. In terms of hardware, the use of high-performance processors, upgraded memory and I/O modules, and optimized power management and anti-interference measures have significantly improved the PLC’s data processing capabilities, response speed and reliability. By choosing a processor with a 50% increase in computing speed and doubled memory capacity, the response speed of the PLC system of an automobile manufacturing company has been greatly improved, and the equipment response delay has been shortened from 100ms to less than 20ms, effectively improving production efficiency.

At the software level, advanced programming technologies such as structured programming and object-oriented programming, as well as intelligent algorithms such as fuzzy control algorithms and neural network algorithms are used to optimize program logic and control strategies, and improve the flexibility and control accuracy of the system. In temperature control, after a chemical production enterprise adopted the fuzzy control algorithm, the temperature deviation was controlled within ±1°C, which effectively improved product quality and reduced the defective rate to less than 5%.

In view of external environmental factors, electromagnetic shielding, grounding technology, and environmental monitoring and control measures are used to reduce the impact of environmental factors such as electromagnetic interference, temperature and humidity on PLC, ensuring its stable operation in complex industrial environments. In the monitoring system of a certain power substation, PLC uses a full metal shielded shell and shielded cables to connect sensors and actuators, effectively resisting strong electromagnetic interference and ensuring the stable operation of the system.

Through actual case analysis of an automobile manufacturing company and a chemical production company, the effectiveness of the optimization measures was verified. After optimization, the production efficiency of automobile manufacturing companies increased by 30%, the product qualification rate increased from 85% to more than 95%, and the equipment failure rate decreased by more than 80%; the production efficiency of chemical production companies increased by 20%, and the defective rate increased from 15% was reduced to less than 5%, and the equipment failure rate was reduced by more than 66%. These remarkable results fully prove that optimizing PLC electrical performance is of great significance for improving production efficiency, product quality and equipment reliability, and can bring huge economic benefits and market competitiveness improvement to enterprises.

7.2 Research deficiencies and prospects

Although this study has achieved certain results in optimizing PLC electrical performance, there are still some shortcomings. The scope of the study is limited in some aspects, mainly focusing on the impact and optimization of common hardware, software and environmental factors on PLC electrical performance. Some emerging technologies, such as the potential application of quantum computing in PLC processors and the application of blockchain technology in PLC data security transmission, have not been deeply explored. With the continuous development of science and technology, these emerging technologies may bring new breakthroughs to the improvement of PLC electrical performance, but this study failed to involve these cutting-edge fields, which limits the comprehensiveness and foresight of the research.

There are also certain limitations in the experimental conditions. During the research process, although actual cases were analyzed, it is difficult for the experimental environment to fully simulate the complex and changeable industrial field environment. Factors such as electromagnetic interference, temperature and humidity changes in industrial sites are often diverse and uncertain, and the experimental conditions may not cover all of these situations. In some special industrial scenarios, such as extreme environments such as deep sea and space, the challenges faced by PLC are more severe. The experimental conditions of this study cannot effectively simulate these extreme situations, which may lead to certain limitations in the promotion of the research results in practical applications.

Future research directions can be developed from multiple aspects. On the one hand, we should explore the application of emerging technologies in the optimization of PLC electrical performance. We should study how quantum computing technology can improve the computing speed and data processing capabilities of PLC processors, and how blockchain technology can enhance the security and reliability of PLC data transmission. We can study how to apply the super computing power of quantum computing to the complex algorithm processing of PLC to achieve rapid analysis and decision-making of large-scale data; and explore how the distributed ledger and encryption technology of blockchain can ensure that the data transmission of PLC in the industrial Internet of Things is not tampered with or stolen.

On the other hand, we will further improve experimental research, expand experimental scenarios, simulate various complex industrial environments as much as possible, and improve the reliability and applicability of research results. We will establish a more comprehensive experimental platform to simulate industrial environments in different industries and scenarios, and test and analyze the performance of PLC under various complex conditions. We will carry out special experimental research in view of the high pressure, low temperature, strong corrosion and other characteristics of the deep-sea environment, as well as the high radiation and microgravity of the space environment, to provide technical support for the application of PLC in these special fields.

With the in-depth development of Industry 4.0 and intelligent manufacturing, PLC will be deeply integrated with artificial intelligence, big data, cloud computing and other technologies. Future research can focus on the impact of these technology integrations on the electrical performance of PLCs, and how to achieve intelligent and adaptive control of PLC control systems through technology integration. Use artificial intelligence technology to achieve intelligent diagnosis and predictive maintenance of PLC production processes, optimize PLC control strategies through big data analysis, and use cloud computing to achieve remote storage and analysis of PLC data. Through the expansion of these research directions, it is expected to further improve the electrical performance of PLCs and provide stronger technical support for the development of industrial automation.

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